Suppr超能文献

调节神经细胞放电模式中序列依赖性的因素:与背侧脊髓小脑束神经元相关的计算机模拟研究

Factors regulating serial dependencies in the discharge patterns of nerve cells: a computer simulation study in relation to dorsal spinocerebellar tract neurones.

作者信息

Harvey R J

出版信息

Brain Res. 1982 Sep 9;247(1):29-38. doi: 10.1016/0006-8993(82)91024-1.

Abstract

This study was undertaken to investigate the factors which may contribute to the strong negative correlation between successive interspike intervals which characteristically occur in the discharge of dorsal spinocerebellar tract (DSCT) neurones. This correlation is reflected by a first-order serial correlation coefficient (R1) which is often less than --0.6(17). This strongly negative correlation would be expected to increase the rate at which the DSCT neurone transmits information from peripheral receptors. A model of a DSCT neurone has been developed and simulated on a digital computer. It was found that the discharge pattern of the model could be very similar to that of a real DSCT neurone and the value of R1 could be less than --0.6. In order for such values of R1 to be generated, a number of conditions had to occur simultaneously. These were that the discharge of the excitatory presynaptic fibres impinging on the neurone had to be fairly regular, that the overall range of firing frequencies on these fibres had to be rather small and that the mean firing rate of the neurone had to be about double that of each presynaptic fibre. Provided these 3 conditions were met, the precise properties of the model were relatively unimportant. Parameter values derived from biophysical studies of real DSCT neurones fulfilled these conditions.

摘要

本研究旨在探讨可能导致背侧脊髓小脑束(DSCT)神经元放电中特征性出现的连续峰间间隔之间强负相关的因素。这种相关性由一阶序列相关系数(R1)反映,该系数通常小于-0.6(17)。这种强负相关预计会提高DSCT神经元从外周感受器传递信息的速率。已在数字计算机上开发并模拟了DSCT神经元模型。发现该模型的放电模式可能与真实DSCT神经元的放电模式非常相似,且R1值可能小于-0.6。为了产生这样的R1值,必须同时满足一些条件。这些条件是:撞击神经元的兴奋性突触前纤维的放电必须相当规则,这些纤维上的放电频率总体范围必须相当小,并且神经元的平均放电率必须约为每条突触前纤维平均放电率的两倍。只要满足这三个条件,模型的精确特性就相对不重要。从真实DSCT神经元的生物物理研究中得出的参数值满足这些条件。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验